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Credit: Rhoda Baer
Worried about the potential for false conclusions in genomics research, a group of scientists created guidelines for distinguishing disease-causing sequence variants from potentially functional variants in the human genome.
In addition to helping researchers confirm variant-disease causality, the guidelines provide recommendations pertaining to genomic study design, databases, and disease diagnosis.
The guidelines are published in Nature.
They were born out of discussions at a 2012 workshop sponsored by the National Human Genome Research Institute.
“Several of us had noticed that studies were coming out with wrong conclusions about the relationship between a specific sequence and disease, and we were extremely concerned that this would translate into inappropriate clinical decisions,” said guideline author Chris Gunter, PhD, of Marcus Autism Center in Atlanta.
In other words, the authors were worried that, based on flawed results, physicians might order additional testing or treatments that are not truly supported by a link between a genetic variant and disease.
As an example, Dr Gunter and her colleagues cited autism research. Investigators found 4 independent variations in the gene TTN when they compared genomes between individuals with and without autism.
However, the TTN gene encodes titin, the largest known protein. So variations are simply more likely in TTN than in other genes. Without applying the proper statistical corrections, researchers may have falsely concluded that TTN was worthy of further investigation in autism studies.
But Dr Gunter believes the new guidelines could help prevent such false conclusions and, therefore, inappropriate medical decisions.
She and her colleagues proposed that researchers do 2 things before concluding that a genetic variation causes a disease. First, they should perform detailed statistical analyses. Then, they should assess evidence from all sources supporting a role for the variant in that specific disease or condition.
The authors said many DNA variants “may suggest a potentially convincing story about how the variant may influence the trait,” but few will actually have causal effects. So using evidence-based guidelines is crucial.
The authors’ guidelines also highlight priorities for research and infrastructure development, including added incentives for researchers to share genetic and clinical data.
“We believe that these guidelines will be particularly useful to scientists and clinicians in other areas who want to do human genomic studies and need a defined starting point for investigating genetic effects,” Dr Gunter said. 
Credit: Rhoda Baer
Worried about the potential for false conclusions in genomics research, a group of scientists created guidelines for distinguishing disease-causing sequence variants from potentially functional variants in the human genome.
In addition to helping researchers confirm variant-disease causality, the guidelines provide recommendations pertaining to genomic study design, databases, and disease diagnosis.
The guidelines are published in Nature.
They were born out of discussions at a 2012 workshop sponsored by the National Human Genome Research Institute.
“Several of us had noticed that studies were coming out with wrong conclusions about the relationship between a specific sequence and disease, and we were extremely concerned that this would translate into inappropriate clinical decisions,” said guideline author Chris Gunter, PhD, of Marcus Autism Center in Atlanta.
In other words, the authors were worried that, based on flawed results, physicians might order additional testing or treatments that are not truly supported by a link between a genetic variant and disease.
As an example, Dr Gunter and her colleagues cited autism research. Investigators found 4 independent variations in the gene TTN when they compared genomes between individuals with and without autism.
However, the TTN gene encodes titin, the largest known protein. So variations are simply more likely in TTN than in other genes. Without applying the proper statistical corrections, researchers may have falsely concluded that TTN was worthy of further investigation in autism studies.
But Dr Gunter believes the new guidelines could help prevent such false conclusions and, therefore, inappropriate medical decisions.
She and her colleagues proposed that researchers do 2 things before concluding that a genetic variation causes a disease. First, they should perform detailed statistical analyses. Then, they should assess evidence from all sources supporting a role for the variant in that specific disease or condition.
The authors said many DNA variants “may suggest a potentially convincing story about how the variant may influence the trait,” but few will actually have causal effects. So using evidence-based guidelines is crucial.
The authors’ guidelines also highlight priorities for research and infrastructure development, including added incentives for researchers to share genetic and clinical data.
“We believe that these guidelines will be particularly useful to scientists and clinicians in other areas who want to do human genomic studies and need a defined starting point for investigating genetic effects,” Dr Gunter said.
Credit: Rhoda Baer
Worried about the potential for false conclusions in genomics research, a group of scientists created guidelines for distinguishing disease-causing sequence variants from potentially functional variants in the human genome.
In addition to helping researchers confirm variant-disease causality, the guidelines provide recommendations pertaining to genomic study design, databases, and disease diagnosis.
The guidelines are published in Nature.
They were born out of discussions at a 2012 workshop sponsored by the National Human Genome Research Institute.
“Several of us had noticed that studies were coming out with wrong conclusions about the relationship between a specific sequence and disease, and we were extremely concerned that this would translate into inappropriate clinical decisions,” said guideline author Chris Gunter, PhD, of Marcus Autism Center in Atlanta.
In other words, the authors were worried that, based on flawed results, physicians might order additional testing or treatments that are not truly supported by a link between a genetic variant and disease.
As an example, Dr Gunter and her colleagues cited autism research. Investigators found 4 independent variations in the gene TTN when they compared genomes between individuals with and without autism.
However, the TTN gene encodes titin, the largest known protein. So variations are simply more likely in TTN than in other genes. Without applying the proper statistical corrections, researchers may have falsely concluded that TTN was worthy of further investigation in autism studies.
But Dr Gunter believes the new guidelines could help prevent such false conclusions and, therefore, inappropriate medical decisions.
She and her colleagues proposed that researchers do 2 things before concluding that a genetic variation causes a disease. First, they should perform detailed statistical analyses. Then, they should assess evidence from all sources supporting a role for the variant in that specific disease or condition.
The authors said many DNA variants “may suggest a potentially convincing story about how the variant may influence the trait,” but few will actually have causal effects. So using evidence-based guidelines is crucial.
The authors’ guidelines also highlight priorities for research and infrastructure development, including added incentives for researchers to share genetic and clinical data.
“We believe that these guidelines will be particularly useful to scientists and clinicians in other areas who want to do human genomic studies and need a defined starting point for investigating genetic effects,” Dr Gunter said.